Simple Linear Regresion - Fixed Model - General Linear Models



Imagen 1 Imagen 2 Imagen 3 Imagen 4

Report - Anova 1 Way - Fixed Model - General Linear Models

1) References

$df_selected_vars
  order var_name var_number var_letter var_role doble_reference
1     1      mpg          1          A       VR         VR(mpg)
2     2      cyl          2          B        X          X(cyl)

2) Linear Regresion - Table

$df_table_reg
            Estimate Std. Error   t value     Pr(>|t|)
(Intercept) 37.88458  2.0738436 18.267808 8.369155e-18
X           -2.87579  0.3224089 -8.919699 6.112687e-10

3) R^2 and Ajusted R^2

$df_table_det_coef
 r.squared adj.r.squared    f.obs df_num df_den p.value
   0.72618     0.7170527 79.56103      1     30       1

4) Position

$df_position
    rol_var var_name  n       min          mean     median       max
1        VR      mpg 32 10.400000  2.009062e+01 19.2000000 33.900000
2         X      cyl 32  4.000000  6.187500e+00  6.0000000  8.000000
3 residuals      --- 32 -4.981416 -2.111755e-16  0.2217446  7.518584

5) Dispersion

$df_dispersion
    rol_var var_name  n range  variance       sd
1        VR      mpg 32  23.5 36.324103 6.026948
2         X      cyl 32   4.0  3.189516 1.785922
3 residuals      --- 32  12.5  9.946266 3.153770

1) Requeriment - Normaility test - Residuals

$test_residuals_normality

    Shapiro-Wilk normality test

data:  minibase_mod$residuals
W = 0.96323, p-value = 0.3359

2) Requeriment - Homogeneity visual evaluation - Residuals

$df_table_plot001
    rol_var var_name  n       min          mean     median       max
1        VR      mpg 32 10.400000  2.009062e+01 19.2000000 33.900000
2         X      cyl 32  4.000000  6.187500e+00  6.0000000  8.000000
3 residuals      --- 32 -4.981416 -2.111755e-16  0.2217446  7.518584

$df_table_plot002
    rol_var var_name  n       min          mean     median       max
1        VR      mpg 32 10.400000  2.009062e+01 19.2000000 33.900000
2         X      cyl 32  4.000000  6.187500e+00  6.0000000  8.000000
3 residuals      --- 32 -4.981416 -2.111755e-16  0.2217446  7.518584